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Mapping aboveground biomass annually across the northwestern USA from lidar and Landsat image time series

Status: 
Action
Dates: 
January, 2015 to October, 2018

Fig. 1. Northwestern USA study area of Washington, Oregon, and Idaho.
Fig. 1. Northwestern USA study area of Washington, Oregon, and Idaho.

The cumulative area of LiDAR collections across multiple ownerships in the northwestern United States has reached the point that land managers of the U.S. Forest Service (USFS) and other stakeholders would greatly benefit from a strategy for how to utilize LiDAR for regional aboveground biomass inventory. The need for Carbon Monitoring Systems (CMS) can be more robustly addressed by using not only available NASA satellite data products, but also commercial airborne LiDAR data collections.

  • We envision a “living” lidar and field plot database of reference observations that can continue to be updated as new project-level forest inventory data are collected. This strategy will actively engage users by utilizing existing data collected by and maintained by land managers of the USFS and other public and private stakeholders.
  • The reference database of field and lidar observations of initial conditions is in a format ready for ingestion into the latest version of the Forest Vegetation Simulator with climate change projection capabilities.

  • Ultimate goal is to develop an objective, accurate, repeatable, and transparent system of carbon monitoring, reporting, and verification (MRV).

Approach

Fig. 2. LiDAR coverage in the northern Idaho preliminary focal area of the study.
Fig. 2. LiDAR coverage in the northern Idaho preliminary focal area of the study.

  • We are using multiple airborne lidar datasets previously acquired at the project level in conjunction with field plot datasets to predict aboveground biomass across the diverse vegetation types of the northwestern United States.

  • Project-level biomass maps will serve as training areas for predicting regional biomass carbon annually from Landsat time series imagery processed through LandTrendr.

  • Regional maps will be validated with the U.S. Forest Service’s Forest Inventory and Analysis (FIA) data summarized annually at the county level.

  • Annual (2000-2012) regional biomass maps will be published on the Oak Ridge National Laboratory’s Data Active Archive Center along with county-level biases.

Key Findings

Fig. 3. First regional map produced in our northern ID preliminary focal area. The year 2012 is predicted, and maps have been generated from 2004-2012
Fig. 3. First regional map produced in our northern ID preliminary focal area. The year 2012 is predicted, and maps have been generated from 2004-2012

  • We have assembled and consistently processed field plot and LiDAR datasets at >53 landscape-level project areas distributed along a broad climate gradient across the northwestern U.S. from temperate rainforest to cold desert (Fig. 1). Twenty of the lidar collections we have assembled to date have accompanying field plot data.

  • 1984-2012 Landsat image time series have been processed through LandTrendr across the entire study region. Landsat image time series have been found to explain more structural variation than can a single scene.

  • We are first developing our prototype modeling approach over a preliminary focal area of northern Idaho (Fig. 2).

  • We are using the Random Forests machine learning algorithm as our predictive modeling approach. The models are explaining  approximately 2/3 of variance in above-ground biomass at both the project and regional levels.

  • Our annually mapped above-ground biomass predictions summarized at the county level are currently about 1.5 times higher than reported independently by the USFS Forest Inventory and Analysis Program. The overestimation bias appears to be related to the proportion of non-forest cover within the county (e.g., Fig. 3).



Project Contact: 

Principal Investigators:
Co-Investigators:
Robert E Kennedy - Oregon State University
Alistair M.S. Smith - University of Minnesota
Michael J Falkowski - Univeristy of Minnesota

Collaborators:
Chris Woodall - Northern Research Station
Van Kane - University of Washington
Nancy Glenn - Boise State University

Research Staff:
Patrick Fekety - University of Minnesota

Funding Contributors:
NASA CArbon Monitoring Systems Program